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. 2021 Feb 10;11(12):6972-6984.
doi: 10.1039/d0ra08593f. eCollection 2021 Feb 4.

Sensor array for wireless remote monitoring of carbon dioxide and methane near carbon sequestration and oil recovery sites

Wesley T Honeycutt  1 , Taehwan Kim  2 , M Tyler Ley  3 , Nicholas F Materer  4
Affiliations

Sensor array for wireless remote monitoring of carbon dioxide and methane near carbon sequestration and oil recovery sites

Wesley T Honeycutt et al. RSC Adv. .

Abstract

Carbon sequestration and enhanced oil recovery are two important geochemical applications currently deployed using carbon dioxide (CO2), a prevalent greenhouse gas. Despite the push to find ways to use and store excess CO2, the development of a large-area monitoring system is lacking. For these applications, there is little literature reporting the development and testing of sensor systems capable of operating in remote areas without maintenance and having significantly low cost to allow their deployment across a large land area. This paper presents the design and validation of a low-cost solar-power distributed sensing architecture using a wireless mesh network integrated, at selective nodes, into a cellular network. This combination allows an "internet of things" approach in remote locations and the integration of a large number of sensor units to monitor CO2 and methane (CH4). This system will allow efficient large area monitoring of both rare catastrophic leaks along with the common micro-seepage of greenhouse gas near carbon sequestration and oil recovery sites. The deployment and testing of the sensor system was performed in an open field at Oklahoma State University. The two-tear network functionality and robustness were determined from a multi-year field study. The reliability of the system was benchmarked by correlating the measured temperature, pressure, and humidity measurement by the network of devices to existing weather data. The CO2 and CH4 gas concentration tracked their expected daily and seasonal cycles. This multi-year field study established that this system can operate in remote areas with minimal human interactions.

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Conflict of interest statement

There are no conflicts to declare.

Figures

Fig. 1
Fig. 1. A generalized representation of the functional blocks within the Tier 1 and 2 nodes. The blocks are: the communication sections (“Mesh Modem” and “Cellular Network”), the “Processing Unit” with local storage, sensors (“Common Sensor Elements” apply to Tier 1 and 2 units, but functional group containing the “Optical Methane Sensor” and its air pump only apply to Tier 1 units), and the “Power System”.
Fig. 2
Fig. 2. Block diagram of the data collection process on a Tier 2 sensor node.
Fig. 3
Fig. 3. Block diagram of the data collection process on a Tier 1 communication node.
Fig. 4
Fig. 4. Communication to the Tier 0 server from each Tier 1 node.
Fig. 5
Fig. 5. This figure shows the averaged results of the sensor network, per hour, after more than 3 years of continual operation. While the majority of measurements center on a site average, there are notable deviations both above and below this region. All reporting units in the network agree, within reasonable tolerance, on these deviations from the average site measurement. Close inspection of the results shown in this figure reveals several gaps in reporting, which indicates that units were powered down for a period before automatically restarting when power reserves reached the critical threshold.
Fig. 6
Fig. 6. Temperature, relative humidity, and atmospheric pressure data from networked sensors was compared with data archived from KSWO. The plots represent the distribution of residuals between the reported KSWO hourly average and the total sensor network hourly average. Each plot includes information about the number of bins, determined by Freedman–Diaconis rule, plus values for relevant statistical descriptions of a fit including mean (μ), standard deviation (σ), skew, and kurtosis.
Fig. 7
Fig. 7. Humidity variation from KSWO occurs more during daylight hours.
Fig. 8
Fig. 8. The average CO2 concentration reported by the sensor network at defined time points produces the expected diel cycle. This plot appears to show notable peaks and troughs outside the average curve, however these likely do not represent realistic events. Fourier analysis suggests that these spikes do not appear consistently, and they likely originate from outliers in the original dataset.
Fig. 9
Fig. 9. A similar diel cycle appears in the average CH4 concentrations reported by the sensor network. The data are noisier than the CO2 data due to limitations of the MQ-4 sensors used in the network. The average concentration, even at the lowest reported points, is noticeably greater than the global baseline for CH4. However, the reported concentration have significant uncertainty as described in the text.
Fig. 10
Fig. 10. The (A) Remote Pro 2.5 W continuous remote power system and (B) Remote Pro 15 W continuous remote power system. Image adapted from Tycon Power Systems' website.
Fig. 11
Fig. 11. The fully built communication node control board.
Fig. 12
Fig. 12. A picture of the sensor board with encapsulating materials removed.
Fig. 13
Fig. 13. Top and side view of the 3D printed part attached to the standoffs on the sensor board, showing the flush interface with the board and the carbon dioxide sensor.
Fig. 14
Fig. 14. Sensors deployed in a field testing site at Oklahoma State University.
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References

    1. Arrhenius S., Philosophical Magazine Series 5, 1896, vol. 41, pp. 237–276
    1. Boden T. A., Marland G. and Andres R. J., Global, Regional, and National Fossil-Fuel CO2 Emissions, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy technical report, 2011
    1. Bachu S. Energy Convers. Manage. 2000;41:953–970. doi: 10.1016/S0196-8904(99)00149-1. - DOI
    1. White C. M. Strazisar B. R. Granite E. J. Hoffman J. S. Pennline H. W. J. Air Waste Manage. Assoc. 2003;53:645–715. doi: 10.1080/10473289.2003.10466206. - DOI - PubMed
    1. Khoo H. H. Tan R. B. H. Environ. Sci. Technol. 2006;40:4016–4024. doi: 10.1021/es051882a. - DOI - PubMed